Digital health is advancing rapidly through new methods, innovative tools, open datasets, and advanced software. These advances transform healthcare delivery, research, education, and patient outcomes. This Research Topic features articles that describe and share these innovations for immediate community use and future development.
We encourage submissions in four focused article types:
Methods Articles introduce new or optimized methods, protocols, or technical approaches essential to digital health. These articles should include a clear abstract, background, step-by-step procedures, required equipment, performance data, and practical discussion. All methods must be described in enough detail for accurate replication.
Curriculum, Instruction, and Pedagogy (CIP) Articles present new curricula, teaching formats, training programs, or educational tools designed for digital health learning and professional development. These articles should document objectives, educational settings, key activities, learner outcomes, and lessons learned. Authors must provide enough information for other educators to adapt or reproduce the innovation.
Data Report Articles describe research datasets relevant to digital health. The dataset must be deposited in a public repository and be open-access. The article should cover the data collection process, applied filters, variables, and guidelines for using and interpreting the data. No study results should be reported—only the structure and availability of the dataset. Study results should be reported separately using the brief research report or original research article type which can be submitted to this collection alongside the data report article.
Technology & Code Articles present new digital tools, software, or code packages relevant to digital health applications or data analysis. These articles should include an accessible abstract, introduction, technical description, example use cases, discussion of scalability, and limitations. Code must be documented, uploaded to a public repository, and accompanied by basic technical specifications and licensing details.
By focusing on these article types, this Research Topic accelerates the sharing of new digital health protocols, educational programs, public datasets, and open-source solutions. The goal is to equip digital health researchers, clinicians, and educators with actionable resources for immediate adoption, further study, and community-driven improvement.
Conflict of Interest Declaration for Topic Editor Prof. Björn Schuller: CSO of audEERING GmbH
Article types and fees
This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:
Brief Research Report
Case Report
Classification
Clinical Trial
Community Case Study
Curriculum, Instruction, and Pedagogy
Data Report
Editorial
FAIR² Data
Articles that are accepted for publication by our external editors following rigorous peer review incur a publishing fee charged to Authors, institutions, or funders.
Article types
This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:
Brief Research Report
Case Report
Classification
Clinical Trial
Community Case Study
Curriculum, Instruction, and Pedagogy
Data Report
Editorial
FAIR² Data
FAIR² DATA Direct Submission
General Commentary
Hypothesis and Theory
Methods
Mini Review
Opinion
Original Research
Perspective
Policy and Practice Reviews
Policy Brief
Review
Study Protocol
Systematic Review
Technology and Code
Keywords: digital health, methods, tools, technology, code, dataset, education, software
Important note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.